https://github.com/lucadiba/renewable-causal-effects

Exploring causal effects of renewable energy on countries development and more. This project is part of course CS 520 Causal Inference and Learning at University of Illinois at Chicago.
https://github.com/lucadiba/renewable-causal-effects

causal-inference renewable-energy

Last synced: 10 days ago
JSON representation

Exploring causal effects of renewable energy on countries development and more. This project is part of course CS 520 Causal Inference and Learning at University of Illinois at Chicago.

• Host: GitHub
• URL: https://github.com/lucadiba/renewable-causal-effects
• Owner: LucaDiba
• Created: 2020-11-03T04:57:39.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2021-02-25T18:43:38.000Z (almost 4 years ago)
• Last Synced: 2024-11-08T18:19:12.502Z (2 months ago)
• Topics: causal-inference, renewable-energy
• Language: Jupyter Notebook
• Homepage:
• Size: 3.21 MB
• Stars: 2
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Causal Effects of Renewable and Fossil Fuel Energy Sectors

## Authors

Luca Dibattista and George Maratos.

## Abstract

In this work we explore causality with real-world data from the United Nations, International Labor Organization, and a few others. Specifically we look at the effects of the energy sector on the economy by disentangling the sources, from which energy is derived, into renewables and fossil fuels (combustibles). We run a case study on the United States, looking at the change in energy production and consumption to find causality with labor statistics and GDP. We find correlations between renewable energy production and both employment in utilities and GDP, while combustible based energy has no direct link. We also have preliminary results on causality for accessibility of electricity, where we determine that renewable energy output is positively correlated with accessibility in a subset of the world's nations. We also run Granger tests to explore the time series component of our data, looking for causality among the variables.

## Project

This is the result of a research work done thanks to Prof. Elena Zheleva during the course CS 520 Causal Inference and Learning at University of Illinois at Chicago.

## Files

In this repository you can find:

- `Causal Effects of Renewable and Fossil Fuel Energy Sectors.pdf`: our paper;

- `reports/`: a folder with the project proposal and the progress report;

- `src/` and `src/scripts/`: a folder with the code we used to write our paper;

- `src/datasets/`: a folder with the datasets we used in our work.